Manager of Data Engineering, Integrations
New
S
SmarterDxHealthcare AI
This role is fully remote within the USFull-TimeManager
Salary190,000 - 210,000 USD per year
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Job Details
- Experience
- 7+ years
- Required Skills
- AWSPythonSQLSnowflakeAirflowData modelingdbt
Requirements
- 7+ years of data engineering experience, including leadership of engineers and outcomes (hiring, mentoring, performance, delivery).
- Deep experience with healthcare datasets: clinical, and/or billing/claims.
- Familiarity with HL7/FHIR and interoperability patterns.
- Strong SQL and data modeling expertise.
- Proven track record building reliable ELT in dbt, Airflow, Snowflake, and Python.
- Operational excellence mindset that integrates SLOs/SLAs, on‑call/incident management, root‑cause analysis, and preventive improvements.
- Demonstrated ability to accelerate client data onboarding through automation, standardization, and repeatable integration patterns.
- Excellent communication and stakeholder management; comfortable driving clarity and alignment across Product, Clinical, and technical partners.
- Willingness to roll up sleeves and contribute hands‑on to unblock the team.
Responsibilities
- Lead, coach, and develop a team of analytics engineers and/or data engineers with a focus on technical excellence, delivery velocity, and collaborative culture.
- Ensure on-time delivery of client data integrations by owning enterprise data model standards and maintaining consistent, governed data definitions.
- Oversee client data pipelines using modern tooling (dbt, Airflow, Snowflake, AWS, Python) to ensure reliable operation and uptime.
- Drive client integration delivery speed by implementing automation, reusable patterns, and clear runbooks to directly optimize client onboarding timelines.
- Establish and enforce SLOs/SLAs, instrument critical paths, and drive incident reduction via proactive monitoring, alerting, and post‑incident reviews.
- Implement comprehensive data quality and testing frameworks (schema, nullability, referential integrity, reconciliation) and lineage observability.
- Collaborate cross‑functionally (Product, Clinical, Data Science, Engineering) to prioritize roadmaps, land measurable outcomes, and manage tradeoffs.
- Manage high-volume client integration requests, triaging and prioritizing tickets based on client impact, urgency, and business value while maintaining clear communication on resolution timelines.
- Own daily operations rhythm including ticket review, resource allocation, escalation management, and stakeholder updates to ensure client integration commitments are met.
- Drive operational metrics and reporting on integration delivery performance, ticket resolution times, and team capacity to identify bottlenecks and improve client outcomes
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